{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "92e3f9ee",
   "metadata": {},
   "source": [
    "### chapter1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e3c5033",
   "metadata": {},
   "source": [
    "<img src=\"img/002.png\" width=600 height=400>\n",
    "<img src=\"img/003.png\" width=600 height=400>\n",
    "<img src=\"img/004.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd91b44a",
   "metadata": {},
   "source": [
    "函数sink(\"filename\")将输出重定向到文件filename中。默认情况下，如果文件已经存在，则它的内容将被覆盖。使用参数append=TRUE可以将文本追加到文件后，而不是覆盖它。参数split=TRUE可将输出同时发送到屏幕和输出文件中。不加参数调用命令sink()将仅向屏幕返回输出结果。\n",
    "\n",
    "`dev.off`：关闭保存图片，直接展示图片。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e3bc6cfe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   mpg cyl disp  hp drat    wt  qsec vs am gear carb\n",
      "Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4\n",
      "Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4\n",
      "Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1\n",
      "Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1\n",
      "Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2\n",
      "Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1\n"
     ]
    }
   ],
   "source": [
    "print(head(mtcars))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2557884b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: grid\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# options(repos = c(CRAN = \"https://mirrors.aliyun.com/CRAN/\"))\n",
    "# install.packages(\"vcd\")\n",
    "# help(package=\"vcd\")\n",
    "library(vcd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7012fc1a-a26c-44a9-8bbc-b3168546658a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "               _                                \n",
       "platform       x86_64-w64-mingw32               \n",
       "arch           x86_64                           \n",
       "os             mingw32                          \n",
       "crt            ucrt                             \n",
       "system         x86_64, mingw32                  \n",
       "status                                          \n",
       "major          4                                \n",
       "minor          4.2                              \n",
       "year           2024                             \n",
       "month          10                               \n",
       "day            31                               \n",
       "svn rev        87279                            \n",
       "language       R                                \n",
       "version.string R version 4.4.2 (2024-10-31 ucrt)\n",
       "nickname       Pile of Leaves                   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4806f369",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Arthrt> data(\"Arthritis\")\n",
      "\n",
      "Arthrt> art <- xtabs(~ Treatment + Improved, data = Arthritis, subset = Sex == \"Female\")\n",
      "\n",
      "Arthrt> art\n",
      "         Improved\n",
      "Treatment None Some Marked\n",
      "  Placebo   19    7      6\n",
      "  Treated    6    5     16\n",
      "\n",
      "Arthrt> mosaic(art, gp = shading_Friendly)\n",
      "\n",
      "Arthrt> mosaic(art, gp = shading_max)\n"
     ]
    },
    {
     "data": {
      "image/png": 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f8p3zCk7FU0hDSetY2fMmvr8peQzuFp7rskpCnXZ23jp8zyuhyEdAiHVxf6zm1Z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\nRK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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T+kc9GOV9xWA/me+baEkOQ+COm18d+8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\n+efKCqTmwgAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# help(Arthritis)\n",
    "example(Arthritis)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "134a95a6",
   "metadata": {},
   "source": [
    "R拥有许多用于存储数据的对象类型，包括标量、向量、矩阵、数组、数据框和列表。\n",
    "\n",
    "<img src=\"img/001.png\" width=400 height=300>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dafbe30e",
   "metadata": {},
   "source": [
    "### chpater2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1d78027",
   "metadata": {},
   "source": [
    "vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c3b22965",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]  1  2  5  3  6 -2  4\n",
      "[1] \"one\"   \"two\"   \"three\"\n",
      "[1]  TRUE  TRUE  TRUE FALSE  TRUE FALSE\n"
     ]
    }
   ],
   "source": [
    "# # vector\n",
    "a <-c(1,2,5,3,6,-2,4)\n",
    "b <-c(\"one\",\"two\",\"three\")\n",
    "c <-c(TRUE,TRUE,TRUE,FALSE,TRUE,FALSE)\n",
    "print(a)\n",
    "print(b)\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd91db51",
   "metadata": {},
   "source": [
    "matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3f626056",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     [,1] [,2] [,3] [,4]\n",
      "[1,]    1    6   11   16\n",
      "[2,]    2    7   12   17\n",
      "[3,]    3    8   13   18\n",
      "[4,]    4    9   14   19\n",
      "[5,]    5   10   15   20\n",
      "   C1 C2\n",
      "R1  1 26\n",
      "R2 24 68\n",
      "[1]  3  8 13 18\n",
      "[1]  6  7  8  9 10\n",
      "[1] 8\n",
      "[1]  1 16\n",
      "[1]  7 12\n",
      "[1] 26\n"
     ]
    }
   ],
   "source": [
    "# matrix\n",
    "y <-matrix(1:20,nrow=5,ncol=4)\n",
    "print(y)\n",
    "cells <-c(1,26,24,68)\n",
    "rnames <-c(\"R1\",\"R2\")\n",
    "cnames <-c(\"C1\",\"C2\")\n",
    "#默认情况下按行填充\n",
    "mymatrix <-matrix(cells,nrow=2,ncol=2,byrow=TRUE,dimnames=list(rnames,cnames))\n",
    "print(mymatrix)\n",
    "print(y[3,])\n",
    "print(y[,2])\n",
    "print(y[3,2])\n",
    "print(y[1,c(1,4)])\n",
    "print(y[2,2:3])\n",
    "print(mymatrix[\"R1\",\"C2\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3004c72",
   "metadata": {},
   "source": [
    "array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "841a7527",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ", , C1\n",
      "\n",
      "   B1 B2 B3\n",
      "A1  1  3  5\n",
      "A2  2  4  6\n",
      "\n",
      ", , C2\n",
      "\n",
      "   B1 B2 B3\n",
      "A1  7  9 11\n",
      "A2  8 10 12\n",
      "\n",
      ", , C3\n",
      "\n",
      "   B1 B2 B3\n",
      "A1 13 15 17\n",
      "A2 14 16 18\n",
      "\n",
      ", , C4\n",
      "\n",
      "   B1 B2 B3\n",
      "A1 19 21 23\n",
      "A2 20 22 24\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#array\n",
    "dim1 <- c(\"A1\",\"A2\")\n",
    "dim2 <- c(\"B1\",\"B2\",\"B3\")\n",
    "dim3 <- c(\"C1\",\"C2\",\"C3\",\"C4\")\n",
    "z <- array(1:24,c(2,3,4),dimnames=list(dim1,dim2,dim3))\n",
    "print(z)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5218ae01",
   "metadata": {},
   "source": [
    "dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8e41db15",
   "metadata": {},
   "outputs": [],
   "source": [
    "patientID <- c(1,2,3,4)\n",
    "age <- c(25,34,28,52)\n",
    "diabetes <- c(\"type1\",\"type2\",\"type1\",\"type1\")\n",
    "status <- c(\"Poor\",\"Improved\",\"Excellent\",\"Poor\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f03e801d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# help(data.frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d4129349",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  patientID age diabetes    status\n",
      "1         1  25    type1      Poor\n",
      "2         2  34    type2  Improved\n",
      "3         3  28    type1 Excellent\n",
      "4         4  52    type1      Poor\n"
     ]
    }
   ],
   "source": [
    "patientdata = data.frame(patientID,age,diabetes,status)\n",
    "print(patientdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ed2dfc70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  patientID age diabetes status\n",
      "1         1  25    type1   Poor\n"
     ]
    }
   ],
   "source": [
    "print(head(patientdata,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e76fc57f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "       \n",
       "        Excellent Improved Poor\n",
       "  type1         1        0    2\n",
       "  type2         0        1    0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#列联表\n",
    "table(patientdata$diabetes,patientdata$status)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "594758ed",
   "metadata": {},
   "source": [
    "- 函数attach()可将数据框添加到R的搜索路径中.\n",
    "- 函数detach()将数据框从搜索路径中移除。值得注意的是，detach()并不会对数据框本身做任何处理。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "18b9fa55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  10.40   15.43   19.20   20.09   22.80   33.90 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAAAM1BMVEX9/v0AAABMTUxnaGd7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\nAoQEAUKCACFBwP9jbB7bzb/M2AAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "attach(mtcars)\n",
    "summary(mpg)\n",
    "plot(mpg,disp)\n",
    "detach(mtcars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fb729143",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  10.40   15.43   19.20   20.09   22.80   33.90 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAAAM1BMVEX9/v0AAABMTUxnaGd7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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#不建议使用attach和detach，可读性太差,宁愿打字多一些\n",
    "summary(mtcars$mpg)\n",
    "plot(mtcars$mpg,mtcars$disp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a51e84c",
   "metadata": {},
   "source": [
    "可以用with创建管道的方式来避免达到attach和detach的效果，如果需要创建在with()结构以外存在的对象，使用特殊赋值符＜＜-替代标准赋值符（＜-）即可，它可将对象保存到with()之外的全局环境中。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c7c39fbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "with(mtcars,{\n",
    "    nokeeepstatus <- summary(mpg)\n",
    "    keepstatus <<- summary(mpg)\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "463ddbd5",
   "metadata": {},
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error: object 'nokeeepstatus' not found\n",
     "output_type": "error",
     "traceback": [
      "Error: object 'nokeeepstatus' not found\nTraceback:\n"
     ]
    }
   ],
   "source": [
    "nokeeepstatus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1db96215",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  10.40   15.43   19.20   20.09   22.80   33.90 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keepstatus"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a42bbaa",
   "metadata": {},
   "source": [
    "实例标识符（case identifier）可通过数据框操作函数中的rowname选项指定（不就是指定某列为primary key?）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d9967788",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  patientID age diabetes    status\n",
      "1         1  25    type1      Poor\n",
      "2         2  34    type2  Improved\n",
      "3         3  28    type1 Excellent\n",
      "4         4  52    type1      Poor\n"
     ]
    }
   ],
   "source": [
    "patientdata <- data.frame(patientID, age, diabetes,status, row.names=patientID)\n",
    "print(patientdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2bf2b5f",
   "metadata": {},
   "source": [
    "因子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "02e7d81e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] Type1 Type2 Type1 Type1\n",
      "Levels: Type1 Type2\n"
     ]
    }
   ],
   "source": [
    "diabetes <- c(\"Type1\", \"Type2\", \"Type1\", \"Type1\")\n",
    "print(factor(diabetes))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5dbb35a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# help(factor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ccaa652a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 1 2 1 1\n",
      "Levels: 1 2\n"
     ]
    }
   ],
   "source": [
    "print(factor(diabetes,labels=c(1,2)))#感觉也就是可以按照指定的方式再次编码"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2b48faac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] Poor      Improved  Excellent Poor     \n",
      "Levels: Poor < Improved < Excellent\n"
     ]
    }
   ],
   "source": [
    "status <- c(\"Poor\", \"Improved\", \"Excellent\", \"Poor\")\n",
    "status <- factor(status, order=TRUE,levels=c(\"Poor\", \"Improved\", \"Excellent\"))#有序型变量可以指定顺序\n",
    "print(status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d370d96a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t4 obs. of  4 variables:\n",
      " $ patientID: num  1 2 3 4\n",
      " $ age      : num  25 34 28 52\n",
      " $ diabetes : chr  \"type1\" \"type2\" \"type1\" \"type1\"\n",
      " $ status   : chr  \"Poor\" \"Improved\" \"Excellent\" \"Poor\"\n"
     ]
    }
   ],
   "source": [
    "str(patientdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0f2204e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "patientdata$diabetes <- factor(diabetes,labels=c(1,2))\n",
    "patientdata$status <- factor(status, order=TRUE,levels=c(\"Poor\", \"Improved\", \"Excellent\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1a50f726",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t4 obs. of  4 variables:\n",
      " $ patientID: num  1 2 3 4\n",
      " $ age      : num  25 34 28 52\n",
      " $ diabetes : Factor w/ 2 levels \"1\",\"2\": 1 2 1 1\n",
      " $ status   : Ord.factor w/ 3 levels \"Poor\"<\"Improved\"<..: 1 2 3 1\n"
     ]
    }
   ],
   "source": [
    "str(patientdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5954d2a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  patientID age diabetes    status\n",
      "1         1  25        1      Poor\n",
      "2         2  34        2  Improved\n",
      "3         3  28        1 Excellent\n",
      "4         4  52        1      Poor\n"
     ]
    }
   ],
   "source": [
    "print(patientdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ea697682",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   patientID         age        diabetes       status \n",
       " Min.   :1.00   Min.   :25.00   1:3      Poor     :2  \n",
       " 1st Qu.:1.75   1st Qu.:27.25   2:1      Improved :1  \n",
       " Median :2.50   Median :31.00            Excellent:1  \n",
       " Mean   :2.50   Mean   :34.75                         \n",
       " 3rd Qu.:3.25   3rd Qu.:38.50                         \n",
       " Max.   :4.00   Max.   :52.00                         "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(patientdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "437e73fa",
   "metadata": {},
   "source": [
    "list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "5208b62f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "$title\n",
      "[1] \"hello R\"\n",
      "\n",
      "$ages\n",
      "[1] 23 25  1\n",
      "\n",
      "[[3]]\n",
      "     [,1] [,2] [,3] [,4]\n",
      "[1,]    1    4    7   10\n",
      "[2,]    2    5    8   11\n",
      "[3,]    3    6    9   12\n",
      "\n",
      "[[4]]\n",
      "[1] \"one\"   \"two\"   \"three\"\n",
      "\n"
     ]
    }
   ],
   "source": [
    "g<- \"hello R\"\n",
    "h <-c(23,25,1)\n",
    "j <- matrix(1:12,nrow=3,ncol=4)\n",
    "k <- c(\"one\",\"two\",\"three\")\n",
    "#是可以指定每个元素的名称的，比如下面的title，ages\n",
    "mylist <- list(title=g,ages=h,j,k)\n",
    "print(mylist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "cf7bb02f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "'hello R'"
      ],
      "text/latex": [
       "'hello R'"
      ],
      "text/markdown": [
       "'hello R'"
      ],
      "text/plain": [
       "[1] \"hello R\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mylist$title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "75bedc96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "'hello R'"
      ],
      "text/latex": [
       "'hello R'"
      ],
      "text/markdown": [
       "'hello R'"
      ],
      "text/plain": [
       "[1] \"hello R\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mylist[[1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e4b8d41f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "'hello R'"
      ],
      "text/latex": [
       "'hello R'"
      ],
      "text/markdown": [
       "'hello R'"
      ],
      "text/plain": [
       "[1] \"hello R\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mylist[[\"title\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e2ef65f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 3 × 4 of type int</caption>\n",
       "<tbody>\n",
       "\t<tr><td>1</td><td>4</td><td>7</td><td>10</td></tr>\n",
       "\t<tr><td>2</td><td>5</td><td>8</td><td>11</td></tr>\n",
       "\t<tr><td>3</td><td>6</td><td>9</td><td>12</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 3 × 4 of type int\n",
       "\\begin{tabular}{llll}\n",
       "\t 1 & 4 & 7 & 10\\\\\n",
       "\t 2 & 5 & 8 & 11\\\\\n",
       "\t 3 & 6 & 9 & 12\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 3 × 4 of type int\n",
       "\n",
       "| 1 | 4 | 7 | 10 |\n",
       "| 2 | 5 | 8 | 11 |\n",
       "| 3 | 6 | 9 | 12 |\n",
       "\n"
      ],
      "text/plain": [
       "     [,1] [,2] [,3] [,4]\n",
       "[1,] 1    4    7    10  \n",
       "[2,] 2    5    8    11  \n",
       "[3,] 3    6    9    12  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mylist[[3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "09e39478",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "$title\n",
      "[1] \"hello R\"\n",
      "\n",
      "$ages\n",
      "[1] 23 25  1\n",
      "\n",
      "[[3]]\n",
      "     [,1] [,2] [,3] [,4]\n",
      "[1,]    1    4    7   10\n",
      "[2,]    2    5    8   11\n",
      "[3,]    3    6    9   12\n",
      "\n",
      "[[4]]\n",
      "[1] \"one\"   \"two\"   \"three\"\n",
      "\n",
      "[[5]]\n",
      "NULL\n",
      "\n",
      "[[6]]\n",
      "[1] 8 6 4\n",
      "\n"
     ]
    }
   ],
   "source": [
    "mylist[[6]] <- c(8,6,4)#指定位置赋值，中间的位置未被赋值将显示null\n",
    "print(mylist)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "822712fb",
   "metadata": {},
   "source": [
    "R中的下标不从0开始，而从1开始。在上述向量中，x[1]的值为8。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae8568e2",
   "metadata": {},
   "source": [
    "R中的函数edit()会自动调用一个允许手动输入数据的文本编辑器。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7e4e84cb",
   "metadata": {},
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in edit(mydata): 'edit()' not yet supported in the Jupyter R kernel\n",
     "output_type": "error",
     "traceback": [
      "Error in edit(mydata): 'edit()' not yet supported in the Jupyter R kernel\nTraceback:\n",
      "1. stop(sQuote(\"edit()\"), \" not yet supported in the Jupyter R kernel\")",
      "2. .handleSimpleError(function (cnd) \n . {\n .     watcher$capture_plot_and_output()\n .     cnd <- sanitize_call(cnd)\n .     watcher$push(cnd)\n .     switch(on_error, continue = invokeRestart(\"eval_continue\"), \n .         stop = invokeRestart(\"eval_stop\"), error = invokeRestart(\"eval_error\", \n .             cnd))\n . }, \"'edit()' not yet supported in the Jupyter R kernel\", base::quote(edit(mydata)))"
     ]
    }
   ],
   "source": [
    "#先创建一个空的dataframe，然后通过调用edit函数去手动输入\n",
    "mydata <- data.frame(age=numeric(0),gender=character(0),weight=numeric(0))\n",
    "mydata <- edit(mydata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54549e11",
   "metadata": {},
   "source": [
    "<img src=\"img/005.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a5c1570",
   "metadata": {},
   "source": [
    "通过fix函数，可以重新编辑输入的表格。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55db140c",
   "metadata": {},
   "source": [
    "直接通过字符串作为输入，其实本质上来看就是类似读取文本文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "422a92bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  age gender weight\n",
      "1  25      m    166\n",
      "2  30      f    115\n",
      "3  18      f    120\n"
     ]
    }
   ],
   "source": [
    "mydatatxt <- \"\n",
    "age gender weight\n",
    "25 m 166\n",
    "30 f 115\n",
    "18 f 120\n",
    "\"\n",
    "mydata <- read.table(header=TRUE, text=mydatatxt)\n",
    "print(mydata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24cb6a14",
   "metadata": {},
   "source": [
    "使用read.table()从带分隔符的文本文件中导入数据(直接报错)，用read.csv()挺好的。\n",
    "\n",
    "函数file()允许你访问文件、剪贴板和C级别的标准输入。函数gzfile()、bzfile()、xzfile()和unz()允许你读取压缩文件。\n",
    "\n",
    "数url()能够让你通过一个含有http://、ftp://或file://的完整URL访问网络上的文件，还可以为HTTP和FTP连接指定代理。为了方便，​（用双引号围住的）完整的URL也经常直接用来代替文件名使用。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15c9dcc6",
   "metadata": {},
   "source": [
    "<img src=\"img/006.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "81e1ccfc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  StudentID First                Last Math Science Social.Studies\n",
      "1        11   Bob               Smith   90      80             67\n",
      "2        12  Jane               Weary   75      NA             80\n",
      "3        10   Dan \"Thornton \\xa2\\xf3\"   65      75             70\n",
      "4        40  Mary           \"O'Leary\"   90      95             92\n"
     ]
    }
   ],
   "source": [
    "file_path <- \"data/studentgrades.csv\"\n",
    "df = read.csv(file_path)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2344b462",
   "metadata": {},
   "outputs": [],
   "source": [
    "# install.packages(\"xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6e268781",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  StudentID First         Last Math Science Social.Studies\n",
      "1       011   Bob        Smith   90      80             67\n",
      "2       012  Jane        Weary   75      NA             80\n",
      "3       010   Dan \"Thornton Ⅲ\"   65      75             70\n",
      "4       040  Mary    \"O'Leary\"   90      95             92\n"
     ]
    }
   ],
   "source": [
    "#读取xlsx\n",
    "library(xlsx)\n",
    "file_path <- \"data/studentgrades.xlsx\"\n",
    "df = read.xlsx(file_path,sheetIndex=1)\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5bdbdf1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NULL"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patientdata$gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "5c21fc7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  patientID age diabetes    status gender\n",
      "1         1  25        1      Poor   male\n",
      "2         2  34        2  Improved female\n",
      "3         3  28        1 Excellent   male\n",
      "4         4  52        1      Poor   male\n"
     ]
    }
   ],
   "source": [
    "patientdata$gender <- c(\"male\",\"female\",\"male\",\"male\")\n",
    "print(patientdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "1e938b94",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  patientID age diabetes    status gender\n",
      "1         1  25        1      Poor      1\n",
      "2         2  34        2  Improved      2\n",
      "3         3  28        1 Excellent      1\n",
      "4         4  52        1      Poor      1\n"
     ]
    }
   ],
   "source": [
    "patientdata$gender <- factor(patientdata$gender,\n",
    "                              labels=c(1,2),levels=c(\"male\",\"female\"))\n",
    "print(patientdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7f63d7c",
   "metadata": {},
   "source": [
    "levels就是dataframe原始的内容，labels就是编码后的值"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39ddef16",
   "metadata": {},
   "source": [
    "<img src=\"img/007.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c923226f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>4</li><li>5</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 4\n",
       "\\item 5\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 4\n",
       "2. 5\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 4 5"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(patientdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "fba55d4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "'data.frame'"
      ],
      "text/latex": [
       "'data.frame'"
      ],
      "text/markdown": [
       "'data.frame'"
      ],
      "text/plain": [
       "[1] \"data.frame\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class(patientdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bdec479",
   "metadata": {},
   "source": [
    "### chpater3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "6c82a3e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EySNwpXhBQOC6WEEVJIqd4uENL35vwh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\ngg==",
      "text/plain": [
       "Plot with title \"regression of mpg on weight\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with (mtcars,{\n",
    "    plot(wt,mpg)\n",
    "    abline(lm(mpg~wt))\n",
    "    title(\"regression of mpg on weight\")\n",
    "    \n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "070d68e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# help(dev.cur)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "080bde2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<strong>pdf:</strong> 2"
      ],
      "text/latex": [
       "\\textbf{pdf:} 2"
      ],
      "text/markdown": [
       "**pdf:** 2"
      ],
      "text/plain": [
       "pdf \n",
       "  2 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with (mtcars,{\n",
    "    pdf(\"data/regression.pdf\")\n",
    "    plot(wt,mpg)\n",
    "    abline(lm(mpg~wt))\n",
    "    title(\"regression of mpg on weight\")\n",
    "    dev.off()\n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88a0393e",
   "metadata": {},
   "source": [
    "出来调用pdf用来保存图片外，最后面要加上dev.off才能正常保存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "5f90121d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAAAM1BMVEX9/v0AAABMTUxnaGd7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\nBAGEBAH+Bz/IF5U/l6teAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dose   <- c(20, 30, 40, 45, 60)\n",
    "drugA <- c(16, 20, 27, 40, 60)\n",
    "drugB <- c(15, 18, 25, 31, 40)\n",
    "plot(dose, drugA, type=\"b\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "80b440bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TkOJaRGmeJYQmqUKY4lJAggJAggJAgg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\nCAkCCAkC/B8GqhpH0XhbswAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "opar <- par(no.readonly=TRUE)\n",
    "# par(lty=2)\n",
    "# par(pch=17)\n",
    "par(lty=2, pch=17)\n",
    "plot(dose, drugA, type=\"b\")\n",
    "par(opar)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cea0237",
   "metadata": {},
   "source": [
    "<img src=\"img/008.png\" width=600 height=400>\n",
    "\n",
    "- pch是plotting character的缩写。它用于指定在绘图中数据点的符号类型。例如，pch = 15表示使用实心方块作为数据点的符号。不同的数字（从 0 到 25 等）代表不同的符号，如圆形、三角形、十字等。\n",
    "\n",
    "- cex是character expansion的缩写。它用于控制绘图符号（由pch指定）和文本的大小。cex的值是一个倍数，例如cex = 2表示将符号和文本的大小设置为默认大小的 2 倍。如果cex = 0.5，则表示将大小设置为默认大小的一半。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bbcc6ac",
   "metadata": {},
   "source": [
    "选项pch=用于指定绘制点时使用的符号\n",
    "\n",
    "<img src=\"img/009.png\" width=300 height=200>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ca3c696",
   "metadata": {},
   "source": [
    "选项lty=用于指定想要的线条类型\n",
    "\n",
    "<img src=\"img/010.png\" width=300 height=200>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "8c68946d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JLzSCxWXSHBQgkJAoQEAUKCACFBgJAg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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(dose, drugA, type=\"p\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "f25345c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tPrdaTlMZ/24ueRkKhOOXc2nBMSlRES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\nIUGAkCBASBAgJAgQEgT8H179rVrWefjfAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(dose, drugA, type=\"b\", lty=3, lwd=3, pch=15, cex=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56c16306",
   "metadata": {},
   "source": [
    "函数rgb()可基于红-绿-蓝三色值生成颜色，而hsv()则基于色相-饱和度-亮度值来生成颜色。\n",
    "\n",
    "参见http://research.stowers-institute.org/efg/R/Color/Chart。 R中也有多种用于创建连续型颜色向量的函数，包括rainbow()、heat.colors()、terrain.colors()、topo.colors()以及cm.colors()。举例来说，rainbow(10)可以生成10种连续的“彩虹型”颜色。\n",
    "\n",
    "<img src=\"img/011.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "3e520450",
   "metadata": {},
   "outputs": [],
   "source": [
    "# options(repos = c(CRAN = \"https://mirrors.aliyun.com/CRAN/\"))\n",
    "# install.packages(\"RColorBrewer\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "a6239f86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AoCCSSQgkACCaT5Hnab748kbR+WF4IE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\nUhBIUhBIUhBIUhBIUhBIUtD/AcgpdC7NjN7dAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(RColorBrewer)\n",
    "n <-7\n",
    "mycolors <- brewer.pal(n, \"Set1\")\n",
    "barplot(rep(1, n), col=mycolors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "f90274d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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V0qpNYdzS/z6Vo53LVA+m169QQvzvSD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\nCgAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n <- 10\n",
    "mycolors <- rainbow(n)\n",
    "pie(rep(1,n),labels=mycolors,col=mycolors)\n",
    "mygrays <- gray(0:n/n)\n",
    "pie(rep(1,n),labels=mygrays,col=mygrays)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aae83bbf-923b-4295-aa49-0a298f797fe2",
   "metadata": {},
   "source": [
    "文本属性\n",
    "\n",
    "<img src=\"img/012.png\" width=600 height=400>\n",
    "\n",
    "`font.lab`:‌1‌：正常样式（默认值）; ‌2‌：加粗; 3‌：倾斜; ‌4‌：加粗倾斜。\n",
    "\n",
    "<img src=\"img/013.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcb3cc84-bff1-4951-9433-5256d9a0cd7b",
   "metadata": {},
   "source": [
    "windows系统中可以使用`windowsFonts`创建字体映射，Mac系统中用`quartzFonts`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35b2ab0f-4777-4fa1-b00e-b09820d90c5b",
   "metadata": {},
   "source": [
    "<img src=\"img/014.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "967afb52-6680-454c-a16d-86fb97c94f00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCA\nkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCA\nkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCA\nkAADhAQYIKS0hBCWfgiYgpDSQkiZIqS0EFKmCCkthJQpQkoLIWWKkNJCSJkipDScd0Uods8h\nHTYhbI63P6+rIoSyqu8L6m37x4e5HybeIaQk7ENvcw+pLsbfufQ3d2G0HRdsh5vFZaEHjBeE\nlILjvZMxpPr2G0Mqh/bX/eGwb+vqn4SuxY8/xvIIKQVtF5tT05zKMIR0vf1G9/Kuvd3+fh/M\npX151/26Gf74vBlvY3GElIDjvYdiCOnxG21CdX/kdH36+vr+x5v+j7E8QkrA9p5DPYT04zeq\nPqficL5/fRXCafinU//HWB4hJaC4P+Fch5B+/EbRvqTrX/MVuzGf8nGOnNd2iSCkBITnMMJ/\n/UZTb4ZzC7vr8HtP5n+8+BchJUAQUvvcdOzeSupP0xFSeggpAY9Xcs1/v7S7uVT9MVFBPckh\npAT8frJh+/yl/Z8/TjYgFYSUgOP9aaccQqqfT38fH+8jjSHVw7tLze2kHpZHSCnorqOrh/df\nh1dtT2/Idont2l+6p6judhdOOfzx9RB4bkoEIaXgdDtxsBtDujzOJXQBPS4JCqF7O+nyuL1b\n9pFjREhJqF8vWr2lUgzHSudbOePty2a8vV/sIeMHQkrDdVf++jGK6767nnWzv18p1H2Motyd\n//mLsAxCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJ\nMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJ\nMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJ\nMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJ\nMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJ\nMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJ\nMEBIgAFCAgwQEmCAkAADhAQYICTAACEBBggJMPB/zYkkWdXgL8IAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dose <- c(20,30,40,45,60)\n",
    "drugA <- c(16,20,27,40,60)\n",
    "drugB <- c(15,18,25,31,40)\n",
    "\n",
    "opar <- par(no.readonly=TRUE)\n",
    "par(pin=c(2,3))\n",
    "par(lwd=2,cex=1.5)\n",
    "par(cex.axis=.75,font.axis=3)\n",
    "\n",
    "plot(dose,drugA,type=\"b\",pch=19,lty=2,col=\"red\",bg=\"green\")\n",
    "plot(dose,drugB,type=\"b\",pch=23,lty=6,col=\"blue\",bg=\"green\")\n",
    "\n",
    "par(opar)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21ce38b9-fe01-40a3-bcc1-f2422edde089",
   "metadata": {},
   "source": [
    "使用title创建自定义的标题，一般用于添加信息到一个默认标题和坐标轴标签被ann=FALSE选项移除的图形中；使用axis创建自定义的坐标轴.\n",
    "\n",
    "<img src=\"img/015.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "4f1ee4e3-f95c-4e36-946d-551890f2e97b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0IaWVn76EneA9iZQ/q2Xtp9a7yGOt8X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\nB6/vXJmgVXqiAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"An Example of Creative Axes\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x <- c(1:10)\n",
    "y <- x\n",
    "z <- 10/x\n",
    "\n",
    "opar = par(no.readonly=TRUE)\n",
    "par(mar=c(5,4,4,8)+0.1)\n",
    "plot(x,y,type=\"b\",pch=21,col=\"red\",yaxt=\"n\",lty=3,ann=FALSE)#yaxt，xaxt参数:是否显示相应坐标轴的标度。yaxt=\"n\"表示不显示y轴的刻度。\n",
    "lines(x,z,type=\"b\",pch=22,col=\"blue\",lty=2)\n",
    "\n",
    "axis(2,at=y,labels=x,col.axis=\"red\",las=2)\n",
    "axis(4,at=z,labels=round(z,digits=2),col.axis=\"blue\",las=2,cex.axis=0.7,tck=-.01)#这里还决定了刻度线的位置,las标签和坐标轴的关系\n",
    "\n",
    "mtext(expression(y == frac(1,x)),side=4,line=2,cex.lab=2,las=2,col=\"blue\")\n",
    "mtext(\"y=x\",side=2,line=2,cex.lab=2,las=2,col=\"black\")\n",
    "\n",
    "# axis(2,at=x,labels=x,col.axis=red)\n",
    "title(\"An Example of Creative Axes\",xlab=\"X value\")\n",
    "par(opar)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65602cb9-c1bf-4f5b-822c-e32d8236494c",
   "metadata": {},
   "source": [
    "使用Hmisc包中的`minor.tick()`函数添加次要刻度线\n",
    "```r\n",
    "library(Hmisc)\n",
    "minor.tick(nx=n, ny=n, tick.ratio=n)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "7eafc99a-74ee-40f0-a1bb-d7c212338ca5",
   "metadata": {},
   "outputs": [],
   "source": [
    "options(repos = c(CRAN = \"https://mirrors.aliyun.com/CRAN/\"))\n",
    "# install.packages(\"Hmisc\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "152c9508-f537-4d62-b683-a09bfb1580f6",
   "metadata": {},
   "source": [
    "`abline()`添加参考线,出来指定参考线的位置，还可以指定参考线的样式\n",
    "```r\n",
    "abline(h=yvalues,v=xvalues)\n",
    "```\n",
    "\n",
    "`legend()`添加图例\n",
    "\n",
    "<img src=\"img/016.png\" width=600 height=400>\n",
    "\n",
    "‌inset distance(s) from the margins as a fraction of the plot region when legend is placed by keyword‌，是指在使用legend()函数时，可以通过inset参数来设置图例与绘图区域边缘的距离。inset参数的值是一个数值或数值向量，表示图例与绘图区域边缘的距离占绘图区域宽度的比例。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "a34860c4-d0c5-4b85-bc8f-03bb9a24bdbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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w0+sI9xJM3QNhqiTaSyRRS+ilepUKo8uvBUc+f51+fL++irG6NNpLIuV84tbUsm\n88+PLUGkVSwUCY8maBOpqVXltUcrttCSBJFWsUgkNJpBu0hVayW0Ua2r7m7pxn6yRCQ8msOQ\nSLY8QqR1LBPJaEieYEakFSOowiDSKpZ2NsAYMyJt2mFVBERaBSJtxYxIgvdYCONIm0CkrRxV\npC4Me/f2kG8i0Tb6BiJBj88i0Vf3Ha0iTRG82TIQaRUfRcKjHyAS9PggEhr9BJGgx7xIePQb\nRIIelUF/E5EshuQJzm9+shNE+sW0f47yZwNHFYlxpGXMdXQj0gaOKlIDIn1hftz1LE99lQWR\nTsun6QuneX6yKIh0Tj5PAjrPg8hFQaQT8nUu3R8mbQGRTsf3Gal/iLQJRDoXv+Z1//1h0iYQ\n6Uz8Xh7xh0nbOKpIjCNNWLLI6A+RNnJUkRoQqWLhWr0/TNoIIp2BpSte//4waSOaRRpPWr1s\nfXDfVhBpsUUFIu3AsEhvQqM7oZxepDXbL4w9wqTlmBdpxSPJBTi3SGxiYgwLIgUma3cnFom9\ngEyiu7MhC4MozYsiTy/qEcqvKAhiwVv+4rQiYZFZNIuUh502kTLpaaZud+5xpIUW0QqSQ7NI\nSW+X1azauths3j6jSCs0QiQpNIt0GT7+NSoQSTNYZAf9nQ158zqvFEIkfSzvX0AjYfSLdG1e\nX5VCj6pcMsWZRKJ/wSKaRSrliZ/lq2dcvlTFUiJ4y1+cRiQssotmkV7DEaSneqSsyaeOnUSk\n5VNSTURzRnSPIyV9jxL1s5EC6Uzd3/QvOID22d/3LkuXnd+Xi9mn9x1fpDXrI0zEc1L0L6PI\n73FYNo8e+dxZ3RxcJHrpXIH1SP7CZDqHQCRfwSKnQCQvoZfONQwvoxC82TIOKRL9C+6BSL6B\nRU7ih0hponr+gjBOFnb+HXQcaXH/AhoZxgORsmSYRrxm04dDiUT/grsY62x4JUGYbkk0HcsY\nBCvSOY5IWOQ0Bnvtbr0lFcvJyzrdNa3n573SsngKl6dzFJEWt4xMBANTDIqUb5pm93h7M5jl\nmr3Nui2+/BAirZlMZyAcmMHkOFIQXNanGVdz9Hrc16xo8l+kpf0LaGQVgyK9NnU2BJMKYb4m\nHd9FWrXZsP5w4BPmRHpGW0VacOjL5etv6QzrNhvWHAx8xWz394ZF5htLpAOMI9FN5xNmRdrQ\n/x0du430r8/kuLWwYC1GRdqyNvY23nb/WL1230T6eTHtIncwJ1IYbxqPVeNIyXAcacV4lK8i\nLYDpdC7h/jKKY89s2CoSFjmG+yIVWTzU6LpmF6Iji6QtKFiPZpFuIo9wyR/d7O903TSjo4oE\njqF972+Tz3CZAZHACPo7GwTT/820PXUkkajPuYtmkULbGdn2/X+xQiT6jGAPnQAAD85JREFU\nF1xGdxtp0yDsiEcUBJdb1zY60hShpSJhkePo7rW7B0Hy3Pcc86geh2r7Lc4qkrGgYD3uLzXv\nOr+biRFeizQyhs6Gg+C8SOV47PVdrUsvrUm+ijRnDCIdBOdFuraPKmsfZOGjSJ9sqQ/+zYpE\nfc4fnBcp7B7n3JjkmUgLSpxZYehf8Annpwj1rXmb9CiWieTIONLCattUGCzyDK9EKk16+lIi\nrWj6zEiDRp7hvEiXrmpXlC2mMPNApJX9B5Q+/qNZpMdVjQJF182TV6/D9YCXt0lOi7ShD+6P\nepz/aBVp/ADZLZR7D/UszMIgdFakjR3ZiHQANIqUhcMeu3DbBId42GNQpbr4alMi7RgM+vvD\nJP/RJ9LYo10m9dO9uCbSvhHVvz9MOgD6RFKNo8tDLWfNUlWubFyblF7Dwc+PyBmRBGYlINIh\n0CbSc9QuUu2lNYvE92FgHElmas/fHyYdAW0ileIMtvoua2TLt9GSQpNIctPjEOkYaBMpHva2\nVbNPza87lxdJdo7p3x8mHQJtIk1qcrmV+Tqyt9wr0VQWRDoIWkUa38pnkXYXRLOy/I0RiBRs\ngEgLEKnN4cmhQaTvbHeIQuZUINJnhAZatwcA/nBUkXaOI8l2zcHxOapI3U1HB/4NmLtk39RT\nSqBzolWkKYI3W8Y6kfYURIh0ahBpemJZyogDPRBpcGJFyogEPRAJQADn92zYySeR/laLRAkE\nXziqSB8Lwdqjv/ktGb+ASPCFo4rUsF0kxIEVnFMkJQgigRyIBCDAKUWqi5qhSJRAsANEakAk\n2MEZRWqVoWoHUpxOJPa/Ah0cVaQvkykQCeQ5qkgN09/v7w+TQBxEAhDgdCL9/WESyINIAAKc\nTaS/MXbCgqNxNpEAtIBIAAIcVSSLi3LhjBxVpAZEAiMgEoAAiAQgACIBCIBIAAIgEoAAiAQg\nwFFFYhwJjHJUkRoQCYyASAACIBKAAIgEIAAiAQiASAACIBKAAH6IlCZxWI4JhXHyyBddwTgS\nGMUDkbJk+PjMOFtxMSKBEdwXKZ0+iTZdfjUigRGcFykv63TX9FX99ErL4ilcVr0rQSQwgvMi\nPd7evPoHsrdZt8WXIxIYwXmR4iC4D4/cgyBafDkigRGcF+ldkxtV5PI1XXGIBEbwQaQFh75c\nLhoNwDw+iLSlRGIcCYzivEgRbSTwAOdFugVBOBiBpdcOHMR5kdQ4UjIcRxpX9r6ASGAE50Vi\nZgP4gPsiFVk81Oj6+n1NCyKBETwQ6V29e3Szv9Pl1boSRAIjeCHSDhAJjHAwkabtKUQCExxM\npAmIBEZAJAABEAlAAEQCEACRAARwXqSZfjiWUYBzHFUkur/BKM6L9IookcB9nBdJrUhaMUt1\nBCKBETwQ6W1SuGZPyAGIBEbwQaQiDOKtlyISGMELkZ7bK3eIBEbwQqQiDi4br0QkMIIfIm0H\nkcAIRxWJcSQwylFFakAkMAIiAQiASAACIBKAAIgEIAAiAQiASAACHFUkxpHAKEcVqQGRwAiI\nBCAAIgEIgEgAAiASgACIBCAAIgEIcFSRGEcCoxxVpAZEAiMgEoAAiAQgACIBCIBIAAIgEoAA\niAQgwFFFYhwJjHJUkRoQCYyASAACIBKAAIgEIAAiAQiASAACIBKAAEcViXEkMMpRRWpAJDAC\nIgEIgEgAAiASgACIBCAAIgEIcFSR6P4GoxxVpAZEAiMgEoAAiAQgACIBCIBIAAIgEoAAiAQg\nwFFFYhwJjHJUkRoQCYyASAACIBKAAIgEIAAiAQiASAACIBKAAEcViXEkMIofIqVJHJZShHHy\nyFddiUhgBA9EypJgQJytuBiRwAjui5QGE9LlVyMSGMF5kfKyTndNX9VPr7QsnsLl1TtEAiM4\nL9Lj7c2rfyB7m3VbfDkigRGcFykOgvvwyD0IosWXIxIYwXmR3jW5UUUuX9OnjUhgBB9EWnCo\nd2qMhpgAxvggEiUSOI/zIkW0kcADnBfpFgThYASWXjtwEOdFUuNIyXAcaVzZ+wIigRGcF4mZ\nDeAD7otUZPFQo+vr9zUtiARG8ECkd/Xu0c3+Tpn9DQ7ihUgbYBwJjHJUkRoQCYyASAACIBKA\nAIgEIAAiAQiASAACIBKAAEcViXEkMMpRRWpAJDDC8UUCMIJgrkUkOC+CudZBkTqCjT/peavT\n93A6OLc/ABkQ6Rj3cDo4tz8AGRDpGPdwOji3PwAZEOkY93A6OLc/ABkQ6Rj3cDo4tz8AGRDp\nGPdwOji3PwAZEOkY93A6OLc/ABkQ6Rj3cDo4tz8AGRDpGPdwOji3PwAZnBZpiJbffztuheNW\nNCcMB5G24lY4bkVzwnAQaStuheNWNCcMB5G24lY4bkVzwnAQaStuheNWNCcMB5G24lY4bkVz\nwnAQaStuheNWNCcMB5G24lY4bkVzwnAQaStuheNWNCcMxyORANwFkQAEQCQAARAJQABEAhAA\nkQAEQCQAARAJQABEAhAAkQAEQCQAARAJQABEAhAAkQAEQCQAARAJQABEAhAAkQAEQCQAARAJ\nQABEAhAAkQAEQCQAARAJQABEAhDAbZFe10sQhNe0PZDfoiAI4kduJZw8cSqcijRo9hG1Gk3Q\nw4Fw6tv3/liaw3FapLj5y8T1gTSsD4Tp1wv1cG/CuWQuhFORtRnXajSviUiWP5zHKO/oDsdl\nkeLuTxOpA1nvj5UZD+fe3TzM7YdTc2kyrjMfThWP5Q/n1t39aiQch0V611mC5P1LZ9f3i0d5\n5G1WeM+L/P7+dklMh5OXf5NX0bu71XBq4rYEsBtNEgTDb3q74bzqP5bKOy8T4Tgs0rXWR70q\ni6S8/TZ5tfUZcyT1d1t7d7vhVNzaEsByNNHoi95yOHH7x7qqV/rDcViksGtFV7/8o/syuY6/\nAPXzrkM17VQXwlE837mkzhiWoxlnT7vhlBW5+o/1zjuhiXAcFqlH9WfqVR9Se5WpKvs6EU4W\nvkvqOgvbjSbrOoQq7IbzGN9Sfzi+iHQpVHn9qg+8xn84c7xudTXBfjhREGaNSHajeefOW357\nF9rRvTpgN5x3qfMcHNAfjhcilX+mol/XK9UKrYSi2iQX9UexHk5VSalFshvN/Z07w373st1w\n4vKrLr2W40iVP/rD8UKkS9XfHAw+DSvN+2q4JHqOQ7ARzqP6eqlvbTea3khFVYmyG055xyak\nZByCnnB8ECmpu+9s59w3ryhWf6BeDrYVTlNFcUKk9zd+rL5dnnE1ymZdpE7tpEAkRdK0Dh0Q\nSZFUYxN2w8nDuobihEg9YvU1Y12k4FIWjK+rqb+V+yK1HrmTV6qxCbvhtAM3ron0VIN+1kWK\n6pem/lbOi9R5ZL9135Cpu1sNp+vPdaKzoY8KyG44QddJZ+pv5bpI116vv/3+5gaVV6yGEwzh\nwxkQjwugs3d/Z5d2mlBhe5Cvj/rjWA1nIpJLH05oO5zrWKSTD8hm7wZ1b2Ct9xEkfcHMEHZT\nhKpmgNVwJiI58+GkqlFiN5y08yYz9LdyWaTSo/5MyG7mYW8ulTGu7TzIsqH/sB1OSzCetGrp\nw7nVLyOViS1/OF07qOpE1B+OyyJdhh6pP1c7F954K0DNzC/jeUb1n8lqOC1NJ5T1D+fWfDiR\n9XDKWfFt97cazNcejsMiPUaVl+EyTPOLxXprxSrB7YbT0IhkN5qk9+Hk9sMpy8WG1Eg4DovU\n+yyazJK2fyw3lppbDaem+WwsR9N+zURufDjtzIbUTDgOizTwaLChRnSztPmJ2k8jHm9+Yiuc\nivazsRxNlgw3G7H94aiNc3p31xyOwyIB+AMiAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgE\nIAAiAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgEIAAiAQiASAAC\nIBKAAIgEIAAiAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgEIAAi\nAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgEIAAiAQiASAACIBKAAIgEIAAiAQiASBYIOuLk\nKZHap5/AFIhkgWBAlO1P7dNPYApEssBQpCDcZxIiuQAiWSAYm7Q7tU8/gSkQyQJdZn89LuUP\niUxq05/AFIhkgUFmT/ZmfURyAUSywDCzl2XSozl6C4PLrf+OXul1DYJLkk9U+STSKylTjpJX\nc+qVRGU9Mk7bA9MUH3HZlfiQ+13PAiJZYJj1H++frvXRe1BZNSNS0vRMLBQpaZtgt+rMresn\nLD6k+AqbVtvuTvmzgUgWGGb9V521m2weF3Mi3dueiWUipb3ODGXFs3fgPp9iNr4GFoNIFhip\nUP+o8m86fkf9Ki//v+ZFFgfLRKorjHlZm7vUB6J3LU8lEM2nWF5zzyvFLnp+9cOCSBb4LFIy\neUf96l4XVUURLROp+T+/JGlevshuF9Vayj+mmDZllaptpgWsAJEs8Fmk5+Qd9au4PZkuE6ms\nr10e+ee7T1O8vv/L2/dcd/2KpwORLPBZpGzyjvpV2B7Il4lU9yREw4Ilf96ijyk2PQ0V1O1W\ngUgWGGb9LOg6G6bv6Fk2e/XHXru2A+5en8kfcWvJbIrBEKnf9hwgkgWG2TQNuu7v6Tt+ixQG\nsyIVSauSqq/dRpIgkiiIZIFhNi3LiUexWKRJ1a5r7BRVX3rc/PBUQ7KVpg9VXbven/nHFEPs\n2Q4iWWCgQjtFaFakV/3qS2dD2UfQNmjivkhv8nv99lKptJ/2NMWBkbAORLJArzBIu0mrfUHC\nJk83mj1aQS5jkZQHoerjfqqehIdKOLlk/ZtN1Jym2B2B1SCSBUaNkXoZRV8QNWr6KvJb01pp\nh0+jafvlMpNa+bborWJemlh2ZYTV9fk9/JxieSp+lcVYM/gES0EkC4w9GhQdinaCTzt9p53Q\nMxmQLbJhv7WqwL36R8qB2EFfgxoumqbYn0W0b2nH+UAkCww9irPuaPuWZspp1yJqBoZmFkpk\nvTLpUrdynq1dYdU0iprb3RvZpil2FzUzXWEhiGSBvkW3V/9o9540Gi9xeL7re9F9fsVRqlZI\nBJdrb/z1Eauq2q2po6Xv68PrS9Xp4k8pNhft3EfifCCSdwTisw7kUzwfiOQJbfN/MFLkVopn\nBpE8oVlHq3q4RVawyqd4ZhDJE+69htW+XYf0pXhmEMkXuqXjO/fB05jiiUEkb2j2LpGrhcmn\neF4QCUAARAIQAJEABEAkAAEQCUAARAIQAJEABEAkAAEQCUAARAIQAJEABEAkAAEQCUAARAIQ\nAJEABEAkAAEQCUAARAIQAJEABEAkAAEQCUAARAIQAJEABEAkAAEQCUAARAIQAJEABEAkAAEQ\nCUAARAIQAJEABEAkAAEQCUAARAIQAJEABEAkAAEQCUAARAIQAJEABEAkAAH+Dw943olOuyee\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"Drug A vs Drug B\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dose <- c(20,30,40,45,60)\n",
    "drugA <- c(16,20,27,40,60)\n",
    "drugB <- c(15,18,25,31,40)\n",
    "\n",
    "opar = par(no.readonly=TRUE)\n",
    "par(lwd=2,cex=1.5,font.lab=2)\n",
    "\n",
    "plot(dose,drugA,type=\"b\",pch=15,lty=1,col=\"red\",ylim=c(0,60),\n",
    "     main=\"Drug A vs Drug B\",xlab=\"Drug Usage\",ylab=\"Drug Response\")\n",
    "lines(dose,drugB,type=\"b\",pch=17,lty=2,col=\"blue\")\n",
    "\n",
    "abline(h=c(30),lty=3,lwd=3,col=\"gray\")\n",
    "\n",
    "library(Hmisc)\n",
    "minor.tick(nx=10, ny=10, tick.ratio=0.5)\n",
    "\n",
    "legend(\"topleft\",legend=c(\"A\",\"B\"),inset=0.05,title=\"Drug Type\",lty=c(1,2),pch=c(15,17),col=c(\"red\",\"blue\"))\n",
    "\n",
    "par(opar)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "587307c8-b41c-4253-8d29-ef9732a6db1f",
   "metadata": {},
   "source": [
    "`type`\n",
    "what type of plot should be drawn. Possible types are\n",
    "\n",
    "- `\"p\"` for points,\n",
    "\n",
    "- `\"l\"` for lines,\n",
    "\n",
    "- `\"b\"` for both,\n",
    "\n",
    "- `\"c\"` for the lines part alone of \"b\",\n",
    "\n",
    "- `\"o\"` for both ‘overplotted’,\n",
    "\n",
    "- `\"h\"` for ‘histogram’ like (or ‘high-density’) vertical lines,\n",
    "\n",
    "- `\"s\"` for stair steps,\n",
    "\n",
    "- `\"S\"` for other steps, see ‘Details’ below,\n",
    "\n",
    "- `\"n\"` for no plotting."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1312164-c23d-4c7d-92b7-cf21b0980aaf",
   "metadata": {},
   "source": [
    "函数`text()`和`mtext()`的选项\n",
    "\n",
    "<img src=\"img/017.png\" width=600 height=400>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "3db07762-4338-49e1-be06-a9072b32b6ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Rlz+PvQ1HO6s6uIkDAzo+6QPe/qW5c9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\nJWjETt0yogAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"Mileage vs. Car Weight\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "attach(mtcars)\n",
    "plot(wt, mpg,\n",
    "    main= \"Mileage vs. Car Weight\",\n",
    "    xlab = \"Weight\", ylab = \"Mileage\",\n",
    "    pch=18,col=\"blue\")\n",
    "text(wt,mpg,labels = row.names(mtcars),cex=0.6,pos=4,col=\"red\")\n",
    "detach(mtcars)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "477adc08-d1fa-4fdd-879a-b380307e5861",
   "metadata": {},
   "source": [
    "`‌mtcars`数据集是R语言中的一个经典数据集，包含了1973-1974年间32款汽车的燃油消耗和其他10种汽车属性的数据‌。该数据集常用于演示统计分析方法，如线性回归、相关性分析等，是学习数据科学和统计学概念的一个很好的资源‌12。\n",
    "\n",
    "`mtcars`数据集的字段含义如下：\n",
    "\n",
    "- `‌mpg`‌：Miles Per Gallon，即每加仑英里数，表示汽车的燃油效率‌。\n",
    "- `‌cyl`‌：Cylinders，表示发动机的气缸数‌。\n",
    "- `disp`‌：Displacement，发动机排量（立方英寸），表示发动机气缸的总容积‌。\n",
    "- `‌hp`‌：Horsepower，总马力，表示汽车产生的功率‌。\n",
    "- `‌drat`‌：Drive Ratio，后轴比率，描述驱动轴的转动与车轮的转动如何对应，较高的值会降低燃油效率‌。\n",
    "- `‌wt`‌：Weight，重量（1000磅），表示汽车的重量‌。\n",
    "-‌ `qsec‌`：1/4 Mile Time，1/4英里加速时间，表示汽车的速度和加速度‌。\n",
    "-‌ `vs`‌：Engine Shape，表示车辆的发动机形状是“V”形还是直形‌。\n",
    "- ‌`am`‌：Transmission，表示汽车的变速箱是自动（0）还是手动（1）‌。\n",
    "- ‌`gear`‌：Number of Gears，前进挡的数量，跑车往往具有更多的挡位‌。\n",
    "- `‌carb‌`：Carburetors，化油器数量，与更强大的发动机相关‌。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "e33b5b0b-3455-4e22-83ae-ea3b43939aff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "opar <- par(no.readonly=TRUE)\n",
    "par(cex=1.5)\n",
    "plot(1:7,1:7,type=\"n\")\n",
    "text(3,3,\"Example of default text\")\n",
    "text(4,4,family=\"mono\",\"Example of mono-spaced text\")\n",
    "text(5,5,family=\"serif\",\"Example of serif text\")\n",
    "par(opar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "59b15f73-74ae-40cc-925d-51f4d68d6548",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nyENI7xLRPV+AhpHONbJqrxEdI4xrdMVOMjpHGMb5moxkdI4xjfMlGNj5DGMb5l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",
      "text/plain": [
       "Plot with title \"手动添加公式\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x <- seq(0, 4, 0.01)\n",
    "y <- sqrt(x)\n",
    "tt <- expression(y == sqrt(x)) # 构建公式\n",
    "plot(x, y, type = 'p', main = \"手动添加公式\",las = 1)\n",
    "text(3,1,labels= tt, cex=1.5,col = \"red\") # 添加公式"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec4ecd44-900f-448a-9c8b-ff5be2ad0c5a",
   "metadata": {},
   "source": [
    "函数`par()`或者`layout`可以容易地组合多幅图形为一幅总图形。\n",
    "\n",
    "- `par()`参数如下：\n",
    "    - mfrow=c(nrows,ncols):按行填充\n",
    "    - mfcol=c(nrows,ncols):按列填充\n",
    "- `layout()`参数如下：\n",
    "    - mat:是一个矩阵，指定多个图形所在的位置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d7dc1b5a-7d30-445c-a473-48be405a28c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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db6JyxfmHQ/muRSnKM4RWiS5jzWcXDb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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"boxplot of wt\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "attach(mtcars)\n",
    "opar <- par(no.readonly=TRUE)\n",
    "par(mfrow=c(2,2),cex=1)\n",
    "plot(wt,mpg,main=\"scatterplot of wt vs.mpg\")\n",
    "plot(wt,disp,main=\"scatterplot of wt vs.disp\")\n",
    "hist(wt,main=\"Histogram of wt\")\n",
    "boxplot(wt,main=\"boxplot of wt\")\n",
    "detach(mtcars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "f492dd6e-a3b1-4eb9-900a-2200cd9c0162",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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URtHHLUVSFNf2QIRkIWiTWyFXLU9bdI2BlrtAf9YyTsjTXagf5ZO+yONbKnfx0J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\nACEBAoQECBASIEBIgAAhAQL/B4hmjw1Bct9JAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"Histogram of disp\""
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with(mtcars,{\n",
    "    layout(matrix(c(1,1,2,3),2,2,byrow=TRUE))\n",
    "    hist(wt)\n",
    "    hist(mpg)\n",
    "    hist(disp)\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ab27fc23-cfde-47a1-b76b-b1982648d668",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.4.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
